Jan 19
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#retrievalaugmentedgeneration AI Developer Masterclass soon: 🚀 https://www.vincibits.com/ai-dev-waiting-list 🚀 Learn how to enhance your systems with this comprehensive rag tutorial. We'll explore techniques that improve retrieval-augmented generation, including leveraging a vector database and metadata filtering. Discover how to implement hybrid search for more effective results and understand what is rag in the context of large language model (llm) applications. TIMESTAMPS: 0:00 - Introduction 0:30 - What is RAG? (Animated Introduction) 1:00 - RAG Basics: Q&A System Overview 1:30 - RAG Pipeline Deep Dive 2:00 - Complete RAG Architecture (Indexing & Retrieval) 2:30 - Naive RAG Drawbacks/Challenges/Pitfalls 4:00 - All 5 Naive RAG Limitations Explained 5:30 - Advanced RAG Benefits Overview 6:00 - Pre-retrieval Strategy 6:30 - Post-retrieval Strategy 7:00 - Advanced Technique #1: Query Expansion (Generated Answers) 7:30 - Query Expansion Flow Diagram 8:30 - Query Expansion Complete Architecture 9:30 - Discussion: When to Use Query Expansion 10:00 - Advanced Technique #2: Query Expansion (Multiple Queries) 10:30 - Multiple Queries Flow Diagram 11:30 - Downsides of Advanced RAG Techniques 13:00 - Advanced Technique #3: Re-ranking (Cross-encoder) 13:30 - Re-ranking Complete Flow Diagram 14:30 - Other Advanced Techniques (Embedding Adaptors, RAG Fusion, etc.) 15:00 - Conclusion & Next Steps